Top Tech Jobs & Startup Jobs in Boston, MA

Design, build, and support scalable cloud data platforms, pipelines, and applications. Develop distributed data solutions using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Establish reusable engineering patterns, data security controls, and operational standards. Collaborate with product, engineering, analytics, and data science teams while mentoring others and communicating technical outcomes to stakeholders. Support resilient, high-performance data workloads and contribute to Agile delivery.

Design, develop, deploy, and support scalable AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, and observability. Optimize model training and inference for cost, latency, throughput, and hardware utilization. Own complex AI architecture, reliability objectives, governance, security, and compliance while collaborating across engineering, research, product, and program teams. Lead technical reviews, shape foundational AI roadmaps, and mentor senior technical staff.

Leads full-stack engineering teams and major technology initiatives, setting technical strategy, managing engineering talent, and delivering reliable cloud-native systems. Oversees distributed microservices, APIs, databases, and scalable software architecture while partnering with product, architecture, and platform leaders. Establishes technology roadmaps, investment priorities, engineering OKRs, succession plans, and organizational strategies. Guides Agile delivery, mentors engineers, evaluates code, and aligns engineering execution with enterprise and regulatory objectives.

Design, develop, deploy, and support large-scale AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Establish enterprise AI architecture standards, optimize model performance and infrastructure costs, lead hybrid and multi-model orchestration, promote responsible AI, and mentor engineering teams while influencing technical strategy and research-to-production processes.

Lead full-stack engineering projects and developers building cloud-based, AI-powered risk management solutions. Design distributed microservices, APIs, databases, and user-facing systems using modern programming languages and AWS technologies. Provide technical leadership across Agile teams, establish engineering standards, mentor engineers, improve system performance, reduce technical debt, and influence long-term technology strategy while supporting regulatory requirements.

Leads multiple technology projects and engineering teams developing distributed microservices, full-stack systems, and cloud-native platforms. Provides technical leadership on architecture, system design, reliability, performance, platform roadmaps, and shared services. Partners with product managers and architects, mentors engineers, drives technology strategy, establishes coding standards, and delivers secure solutions supporting regulatory and compliance needs.

Design, develop, optimize, deploy, and support foundational AI systems, including LLMs, agents, vector search, model evaluation, orchestration pipelines, and responsible AI controls. Lead cost-performance governance, technical design reviews, roadmap development, and optimization of model and hardware utilization. Mentor senior AI engineers while partnering with research, product, program, and engineering teams to deliver scalable production AI platforms.

Lead full-stack engineering projects and development teams building cloud-based, distributed microservices and full-stack systems. Provide technical leadership, establish engineering standards, mentor developers, define service architectures, improve system performance, reduce technical debt, and influence long-term technology strategy. The role uses multiple programming languages, databases, AWS services, Docker, Kubernetes, CI/CD, infrastructure as code, automated testing, and modern AI development tools.

Design, develop, deploy, and support scalable AI systems, including foundation models, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Establish enterprise AI architecture standards, optimize model performance and infrastructure costs, guide hybrid and multi-cloud strategies, and promote responsible AI practices. Lead technical direction, mentor engineering teams, collaborate with cross-functional stakeholders, and advance research techniques into production.

Lead engineering projects and developers building cloud-based, AI-powered risk management solutions. Design and deploy full-stack microservices, APIs, and distributed systems using modern programming languages, databases, AWS services, containers, and messaging technologies. Provide technical leadership across Agile teams, establish engineering standards, mentor engineers, partner with architects and product managers, reduce technical debt, improve system performance, and influence long-term technology strategy.